HsiaoFeng C.

－ Led and collaborated closely with front-end and backend engineering teams, ML team, DS team, and BI team to determine the end-to-end data solutions with structured and unstructured event streams from S3 (Snow Stage -> Pipe -> Stream -> Task) or Segment into a governed Snowflake data lake and analytical layer, enabling cross-functional workflows for ML, Data Science, and BI teams. － Redesigned enterprise-wide Data Governance by implementing a scalable Snowflake RBAC hierarchy (Database Role -> Team/Functional Role -> User) to ensure rigorous PII protection and international data privacy compliance (GDPR). － Engineered the Customer 360 data pipeline using Segment and Snowflake, unifying fragmented touchpoints into a cohesive user journey to enable advanced lifecycle analytics and high-fidelity attribution across the entire marketing funnel. － Governed Segment event tracking schema in partnership with MarTech and Product — standardizing event naming, payload structure, and marketing attributes (UTMs, identifiers) to ensure reliable, consistent data across all downstream analytics and attribution models. － Established Data Observability by building micro-batch monitoring and validation frameworks (Streamlit, Snowsight, and Looker), reducing anomaly detection time to under two hours and ensuring the reliability of core Customer 360 datasets. － Standardized Orchestration by deploying a production-grade Airflow service following software engineering best practices, including CI/CD integration, environment-level isolation, and secure secret management.

－ Optimized Performance Engineering, slashing critical ELT pipeline runtimes by 92% (from 6 hours to 30 minutes) through advanced SQL tuning, micro partitioning, and the implementation of Snowflake Streams and Tasks. － Architected the Daily Marketing Attribution (DMA) engine, processing trillions of daily events to provide a unified source of truth for global marketing performance, enabling regional teams in NA and EU to optimize multi-channel campaign spend. － Engineered Data Activation (Reverse ETL) pipelines to synchronize high-fidelity customer segments from the data warehouse to external marketing and growth platforms (e.g., Segment and iterable). － Advanced Data Modeling: Developed historical state-tracking models using SCD Type 2 (Time-Travel) logic to provide high-integrity training datasets for machine learning models. － Unified Metric Logic by abstracting complex business calculations into standardized API-like functions within dbt, ensuring metric consistency and preventing logic drift across all data sources. － Strengthened Data Integrity by enforcing Data Contracts and comprehensive dbt testing suites, treating the data warehouse as a high-reliability product for 200+ stakeholders.

－ Assisted the data engineering team in reading the JavaScript legacy data pipelines. － Introduced SQL optimization techniques in the team.

－ Pioneered a "0 to 1" Data Ecosystem (BigQuery, Airflow, Tableau), transitioning the organization to a data-driven culture and establishing company-wide communication standards for metrics. － Architected Scalable Ingestion Pipelines (from MySQL, GA4, Firebase, and UTM parameters) to unify disparate product and marketing telemetry, delivering insights that directly empowered growth initiatives, accounting for ~30% of annual revenue. － Engineered Fault-Tolerant Workflows with automated fallback strategies and integrity checks in Airflow, ensuring high data freshness and zero-downtime reporting. - Developed advanced URL parsing logic to track the full user journey, enabling Marketers and Product Managers to quantify the ROI of ad spend and measure the true impact of feature launches through granular attribution modeling. － Empowered Self-Service Analytics by designing advanced Tableau applications utilizing complex LOD expressions and user-centric UI design to streamline exploratory analysis. － Developed a fraud detection framework for the Finance team utilizing Python, Tableau, and Google Sheets to identify and mitigate revenue-impacting anomalies. - Mentored and enabled data-driven decision-making across the organization by developing governed self-service frameworks; consulted on metric definition and tool adoption to ensure high-reliability insights.

Attached to the undergraduate courses in Computer Science Department with a certificate: - discrete mathematics (94/100) - linear algebra (86/100) - computer programming I (89/100) - computer algorithm (89/100)